segnale-e-rumore/infografica2_trappola_cognitiva.html at main · salvofedele/segnale-e-rumore · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
<!DOCTYPE html>
<html lang="it">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Infografica 2 — La Trappola Cognitiva</title>
<link href="https://fonts.googleapis.com/css2?family=Syne:wght@700;800&family=IBM+Plex+Mono:wght@400;600&family=Syne+Mono&family=Lora:ital,wght@0,400;1,400&display=swap" rel="stylesheet">
<style>
  :root {
    --bg: #f5f0e8;
    --dark: #1a1208;
    --red: #d93025;
    --orange: #e87722;
    --blue: #1a56db;
    --green: #1b7340;
    --paper: #ede8dc;
    --paper2: #e4ddd0;
    --ink: #2d2413;
    --muted: #7a6e5f;
  }
  * { margin:0; padding:0; box-sizing:border-box; }
  body {
    background: var(--bg);
    color: var(--dark);
    font-family: 'Lora', serif;
    min-height: 100vh;
    overflow-x: hidden;
  }

  /* HEADER — brutalist stamp */
  .header {
    background: var(--dark);
    padding: 50px 60px 40px;
    position: relative;
    overflow: hidden;
  }
  .header::after {
    content: 'ATTENZIONE';
    position: absolute;
    top: -20px; right: -30px;
    font-family: 'Syne', sans-serif;
    font-size: 180px;
    font-weight: 800;
    color: rgba(255,255,255,0.03);
    letter-spacing: -10px;
    pointer-events: none;
  }
  .header-eyebrow {
    font-family: 'IBM Plex Mono', monospace;
    font-size: 11px;
    letter-spacing: 4px;
    color: var(--orange);
    margin-bottom: 20px;
    text-transform: uppercase;
  }
  .header h1 {
    font-family: 'Syne', sans-serif;
    font-size: clamp(32px, 5vw, 64px);
    font-weight: 800;
    color: #f5f0e8;
    line-height: 1;
    max-width: 800px;
  }
  .header h1 em { color: var(--orange); font-style: normal; }
  .header-sub {
    margin-top: 18px;
    color: rgba(245,240,232,0.55);
    font-size: 14px;
    line-height: 1.7;
    max-width: 580px;
  }

  /* MAIN */
  .main { padding: 48px 60px; }

  /* THE ILLUSION SECTION */
  .illusion-banner {
    background: var(--paper);
    border: 2px solid var(--ink);
    border-radius: 0;
    padding: 36px 40px;
    margin-bottom: 32px;
    display: grid;
    grid-template-columns: 1fr auto 1fr;
    gap: 32px;
    align-items: center;
    animation: slideIn 0.5s ease both;
  }
  .num-big {
    font-family: 'Syne', sans-serif;
    font-weight: 800;
    line-height: 1;
    text-align: center;
  }
  .num-big.ok { font-size: 80px; color: var(--green); }
  .num-big.warn { font-size: 80px; color: var(--red); }
  .num-label {
    font-family: 'IBM Plex Mono', monospace;
    font-size: 10px;
    letter-spacing: 2px;
    text-transform: uppercase;
    color: var(--muted);
    text-align: center;
    margin-top: 8px;
  }
  .arrow-col {
    display: flex;
    flex-direction: column;
    align-items: center;
    gap: 8px;
  }
  .arrow-sym {
    font-family: 'Syne', sans-serif;
    font-size: 48px;
    color: var(--orange);
  }
  .arrow-note {
    font-family: 'IBM Plex Mono', monospace;
    font-size: 10px;
    letter-spacing: 1px;
    color: var(--muted);
    text-align: center;
    max-width: 100px;
  }

  /* THEOREM BOXES */
  .theorem-grid {
    display: grid;
    grid-template-columns: 1fr 1fr;
    gap: 20px;
    margin-bottom: 32px;
  }
  .theorem-card {
    border: 2px solid var(--ink);
    padding: 28px;
    position: relative;
    animation: slideIn 0.5s 0.15s ease both;
    background: var(--paper);
  }
  .theorem-card.bad { border-color: var(--red); background: #fdf1f0; }
  .theorem-card.good { border-color: var(--green); background: #f0fdf4; }

  .tc-corner {
    position: absolute;
    top: -2px; left: -2px;
    width: 40px; height: 40px;
    display: flex; align-items: center; justify-content: center;
  }
  .tc-corner.bad { background: var(--red); }
  .tc-corner.good { background: var(--green); }
  .tc-icon { font-size: 18px; }

  .tc-title {
    font-family: 'Syne', sans-serif;
    font-size: 14px;
    font-weight: 700;
    text-transform: uppercase;
    letter-spacing: 1px;
    margin-bottom: 14px;
    margin-top: 24px;
  }
  .tc-title.bad { color: var(--red); }
  .tc-title.good { color: var(--green); }

  .tc-body { font-size: 14px; line-height: 1.7; color: var(--ink); }
  .tc-highlight {
    font-family: 'IBM Plex Mono', monospace;
    font-size: 13px;
    padding: 10px 14px;
    margin-top: 14px;
    border-left: 3px solid;
    background: rgba(0,0,0,0.04);
  }
  .tc-highlight.bad { border-color: var(--red); }
  .tc-highlight.good { border-color: var(--green); }

  /* Bayes visual */
  .bayes-section {
    background: var(--dark);
    color: var(--bg);
    padding: 40px;
    margin-bottom: 32px;
    position: relative;
    animation: slideIn 0.5s 0.25s ease both;
  }
  .bayes-title {
    font-family: 'Syne', sans-serif;
    font-size: 20px;
    font-weight: 800;
    color: var(--orange);
    margin-bottom: 28px;
    text-transform: uppercase;
    letter-spacing: 2px;
  }

  .bayes-row {
    display: grid;
    grid-template-columns: repeat(3, 1fr);
    gap: 24px;
  }
  .bayes-block {
    border: 1px solid rgba(245,240,232,0.15);
    padding: 22px;
  }
  .bayes-block-title {
    font-family: 'IBM Plex Mono', monospace;
    font-size: 9px;
    letter-spacing: 3px;
    color: var(--orange);
    text-transform: uppercase;
    margin-bottom: 14px;
  }
  .bayes-val {
    font-family: 'Syne', sans-serif;
    font-size: 36px;
    font-weight: 700;
    color: var(--bg);
  }
  .bayes-desc {
    font-size: 12px;
    color: rgba(245,240,232,0.55);
    margin-top: 8px;
    line-height: 1.5;
  }

  .formula-box {
    background: rgba(255,255,255,0.05);
    border: 1px solid rgba(232,119,34,0.5);
    padding: 16px 24px;
    margin-top: 28px;
    font-family: 'IBM Plex Mono', monospace;
    font-size: 13px;
    color: var(--orange);
    line-height: 2;
  }

  /* Age comparison */
  .age-compare {
    background: var(--paper2);
    border: 2px solid var(--ink);
    padding: 36px 40px;
    margin-bottom: 32px;
    animation: slideIn 0.5s 0.3s ease both;
  }
  .age-compare-title {
    font-family: 'Syne', sans-serif;
    font-size: 18px;
    font-weight: 800;
    text-transform: uppercase;
    letter-spacing: 2px;
    margin-bottom: 28px;
    border-bottom: 2px solid var(--ink);
    padding-bottom: 14px;
  }
  .age-rows { display: grid; grid-template-columns: 1fr 1fr; gap: 20px; }
  .age-block {
    padding: 24px;
    border: 2px solid;
  }
  .age-block.t21 { border-color: var(--green); background: #f0fdf4; }
  .age-block.xxу { border-color: var(--red); background: #fdf1f0; }
  .age-block-label {
    font-family: 'IBM Plex Mono', monospace;
    font-size: 10px;
    letter-spacing: 2px;
    text-transform: uppercase;
    margin-bottom: 12px;
  }
  .age-block.t21 .age-block-label { color: var(--green); }
  .age-block.xxу .age-block-label { color: var(--red); }
  .age-block h4 {
    font-family: 'Syne', sans-serif;
    font-size: 16px;
    font-weight: 800;
    margin-bottom: 10px;
  }

  .prevalence-bar-wrap { margin: 16px 0 8px; }
  .prev-label {
    font-family: 'IBM Plex Mono', monospace;
    font-size: 10px;
    color: var(--muted);
    margin-bottom: 6px;
  }
  .prev-bar-row {
    display: flex; align-items: center; gap: 10px; margin-bottom: 8px;
  }
  .prev-bar-bg {
    flex: 1; height: 14px;
    background: rgba(0,0,0,0.08);
    border-radius: 2px;
    overflow: hidden;
  }
  .prev-bar-fill { height: 100%; border-radius: 2px; }
  .prev-val {
    font-family: 'Syne', sans-serif;
    font-weight: 700;
    font-size: 13px;
    min-width: 54px;
  }
  .prev-age {
    font-family: 'IBM Plex Mono', monospace;
    font-size: 10px;
    color: var(--muted);
    min-width: 54px;
  }

  .verdict-box {
    background: var(--dark);
    color: var(--bg);
    padding: 28px 36px;
    border-left: 6px solid var(--orange);
    font-size: 16px;
    line-height: 1.7;
    animation: slideIn 0.5s 0.4s ease both;
  }
  .verdict-box strong { color: var(--orange); }

  @keyframes slideIn {
    from { opacity:0; transform: translateX(-20px); }
    to   { opacity:1; transform: translateX(0); }
  }

  @media (max-width: 900px) {
    .main, .header { padding: 24px 20px; }
    .illusion-banner { grid-template-columns: 1fr; }
    .theorem-grid { grid-template-columns: 1fr; }
    .bayes-row { grid-template-columns: 1fr; }
    .age-rows { grid-template-columns: 1fr; }
  }
</style>
</head>
<body>

<div class="header">
  <div class="header-eyebrow">Infografica II · Ragionamento Bayesiano in Medicina Prenatale</div>
  <h1>La <em>Trappola</em><br>Cognitiva del<br>99.86%</h1>
  <p class="header-sub">Come numeri apparentemente eccellenti — sensibilità 93%, specificità 99,86% — nascondono una realtà clinicamente pericolosa per chi non applica il Teorema di Bayes.</p>
</div>

<div class="main">

  <!-- The core illusion -->
  <div class="illusion-banner">
    <div>
      <div class="num-big ok">99.86%</div>
      <div class="num-label">Specificità</div>
      <div style="text-align:center; margin-top:12px; font-size:13px; color:var(--green); font-style:italic;">
        "Il test è quasi perfetto!"
      </div>
    </div>
    <div class="arrow-col">
      <div class="arrow-sym">≠</div>
      <div class="arrow-note">Non significa quello che pensiamo</div>
    </div>
    <div>
      <div class="num-big warn">48%</div>
      <div class="num-label">Falsi Positivi a 40 anni (1−PPV)</div>
      <div style="text-align:center; margin-top:12px; font-size:13px; color:var(--red); font-style:italic;">
        Quasi 1 su 2 è falso!
      </div>
    </div>
  </div>

  <!-- Theorem cards -->
  <div class="theorem-grid">
    <div class="theorem-card bad">
      <div class="tc-corner bad"><div class="tc-icon" style="color:white">✗</div></div>
      <div class="tc-title bad">Ragionamento Sbagliato</div>
      <div class="tc-body">
        "Il NIPT ha specificità 99,86% e il test è positivo per XXY. Questa donna ha 41 anni, quindi la probabilità che il feto abbia davvero XXY è elevatissima."
      </div>
      <div class="tc-highlight bad">
        <strong>Errore:</strong> si ignora la prevalenza di partenza di XXY (~1/660 maschi nati) e si confonde la specificità del test con il valore predittivo positivo.
      </div>
    </div>
    <div class="theorem-card good">
      <div class="tc-corner good"><div class="tc-icon" style="color:white">✓</div></div>
      <div class="tc-title good">Ragionamento Corretto (Bayesiano)</div>
      <div class="tc-body">
        La specificità dice quanti sani vengono correttamente classificati negativi. Su 10.000 sani testati, 14 risulteranno positivi per errore. Se la prevalenza è bassa, quei 14 falsi positivi possono superare i veri positivi.
      </div>
      <div class="tc-highlight good">
        <strong>PPV = TP / (TP + FP)</strong> — dipende dalla prevalenza. Per XXY, la prevalenza non cresce con l'età materna come la T21.
      </div>
    </div>
  </div>

  <!-- Bayes section -->
  <div class="bayes-section">
    <div class="bayes-title">Calcolo del PPV — 47,XXY in una donna di 41 anni</div>
    <div class="bayes-row">
      <div class="bayes-block">
        <div class="bayes-block-title">Prevalenza XXY (maschi)</div>
        <div class="bayes-val">1/660</div>
        <div class="bayes-desc">≈ 0.15% tra i nati maschi. <strong>NON aumenta significativamente con l'età materna</strong>, a differenza della Trisomia 21.</div>
      </div>
      <div class="bayes-block">
        <div class="bayes-block-title">Su 10.000 gravidanze maschili testate</div>
        <div class="bayes-val">~15</div>
        <div class="bayes-desc">feti XXY attesi. Il test a sensibilità 93% ne trova ≈ 14. Con spec. 99,86%: <strong>~14 falsi positivi</strong> tra i 9985 sani.</div>
      </div>
      <div class="bayes-block">
        <div class="bayes-block-title">PPV risultante</div>
        <div class="bayes-val">~50%</div>
        <div class="bayes-desc">14 veri positivi / (14 veri + 14 falsi) ≈ 50%. <strong>Metà dei positivi sono falsi</strong>, malgrado specificità 99.86%.</div>
      </div>
    </div>
    <div class="formula-box">
      PPV = (Sensibilità × Prevalenza) / [(Sensibilità × Prevalenza) + ((1−Specificità) × (1−Prevalenza))]<br>
      PPV ≈ (0.93 × 0.0015) / [(0.93 × 0.0015) + (0.0014 × 0.9985)] ≈ <strong>50%</strong>
    </div>
  </div>

  <!-- Age comparison: T21 vs XXY -->
  <div class="age-compare">
    <div class="age-compare-title">Il contrasto che svela la trappola: T21 vs XXY</div>
    <div class="age-rows">
      <div class="age-block t21">
        <div class="age-block-label">Trisomia 21 — sensibile all'età</div>
        <h4>Il PPV cresce con l'età ✓</h4>
        <div class="prevalence-bar-wrap">
          <div class="prev-label">Prevalenza alla nascita per età materna</div>
          <div class="prev-bar-row">
            <span class="prev-age">20 anni</span>
            <div class="prev-bar-bg"><div class="prev-bar-fill" style="width:3%; background:var(--green)"></div></div>
            <span class="prev-val" style="color:var(--green)">1/1500</span>
          </div>
          <div class="prev-bar-row">
            <span class="prev-age">35 anni</span>
            <div class="prev-bar-bg"><div class="prev-bar-fill" style="width:18%; background:var(--green)"></div></div>
            <span class="prev-val" style="color:var(--green)">1/270</span>
          </div>
          <div class="prev-bar-row">
            <span class="prev-age">41 anni</span>
            <div class="prev-bar-bg"><div class="prev-bar-fill" style="width:62%; background:var(--green)"></div></div>
            <span class="prev-val" style="color:var(--green)">~1/70</span>
          </div>
        </div>
        <div style="font-size:13px; color:var(--green);">PPV sale: 48% → 93%<br>L'età materna <em>aiuta</em> il test.</div>
      </div>
      <div class="age-block xxу">
        <div class="age-block-label">47,XXY — insensibile all'età</div>
        <h4>Il PPV rimane basso ✗</h4>
        <div class="prevalence-bar-wrap">
          <div class="prev-label">Prevalenza alla nascita per età materna</div>
          <div class="prev-bar-row">
            <span class="prev-age">20 anni</span>
            <div class="prev-bar-bg"><div class="prev-bar-fill" style="width:22%; background:var(--red)"></div></div>
            <span class="prev-val" style="color:var(--red)">~1/660</span>
          </div>
          <div class="prev-bar-row">
            <span class="prev-age">35 anni</span>
            <div class="prev-bar-bg"><div class="prev-bar-fill" style="width:22%; background:var(--red)"></div></div>
            <span class="prev-val" style="color:var(--red)">~1/660</span>
          </div>
          <div class="prev-bar-row">
            <span class="prev-age">41 anni</span>
            <div class="prev-bar-bg"><div class="prev-bar-fill" style="width:22%; background:var(--red)"></div></div>
            <span class="prev-val" style="color:var(--red)">~1/660</span>
          </div>
        </div>
        <div style="font-size:13px; color:var(--red);">PPV a 40 anni: 52% (SMFM) → ancora insufficiente.<br>L'età materna <em>non aiuta</em> il PPV per XXY.</div>
      </div>
    </div>
  </div>

  <div class="verdict-box">
    <strong>La trappola in una frase:</strong> il clinico matura un'aspettativa di alta accuratezza predittiva dal NIPT basandosi sull'esperienza con T21 in età avanzata (PPV 93%). Applica mentalmente la stessa logica a XXY in una donna di 41 anni — e si sbaglia. La specificità 99,86% suona come "quasi impossibile che sia falso", ma quando la prevalenza di base non cresce, <strong>metà dei positivi rimangono falsi</strong>. È la legge di Bayes, non un difetto del test.
  </div>

</div>
</body>
</html>